Risk assessment of oil and gas investment environment in countries along the Belt and Road Initiative

With the implementation of the Belt and Road Initiative, China is deepening its cooperation in oil and gas resources with countries along the Initiative. In order to better mitigate risks and enhance the safety of investments, it is of significant importance to research the oil and gas investment environment in these countries for China's overseas investment macro-layout. This paper proposes an indicator system including 27 indicators from 6 dimensions. On this basis, game theory models combined with global entropy method and analytic hierarchy process are applied to determine the combined weights, and the TOPSIS-GRA model is utilized to assess the risks of oil and gas investment in 76 countries along the Initiative from 2014 to 2021. Finally, the GM(1,1) model is employed to predict risk values for 2022-2025. In conclusion, oil and gas resources and political factors have the greatest impact on investment environment risk, and 12 countries with greater investment potential are selected through cluster analysis in conjunction with the predicted results. The research findings may provide scientific decisionmaking recommendations for the Chinese government and oil enterprises to strengthen oil and gas investment cooperation with countries along the Belt and Road Initiative.

Are cities greener because of innovation?Independent innovation policy and green economic efficiency

The national independent innovation demonstration zone(NIIDZ)is an independent innovation policy that plays a crucial role in implementing strategies.Given the importance of the NIIDZ,this study uses panel data of 278 prefecture-level cities in China from 2006 to 2020 and empirically examines the effect and internal mechanism of the NIIDZ on green economic efficiency(GEE)using the difference-in-difference model(DID).The results show that the NIIDZ effectively enhances the growth of GEE,and the results remain valid through several robustness tests,such as year-by-year propensity score matching.The transmission mechanism suggests that the NIIDZ indirectly drives GEE by accelerating scientific and technological investment,promoting talent concentration,and optimizing the industrial structure.Moreover,heterogeneity analysis reveals that the promotion effect of the NIIDZ on GEE is more prominent in the eastern region and high green development level areas.The study’s findings can serve as a reference for China to further utilize the policy effectiveness of the NIIDZ and accelerate the high-quality development of the green economy in the future.

Spatio-temporal evolution of the coordinated development of high-tech industry agglomeration and resource-environmental carrying capacity in the Yellow River Basin

Under the background of new infrastructure,the Yellow River Basin’s superior growth cannot be separated originating with the synergistic effect of scientific and technological inventiveness and ecological civilization construction.In light of the coupling coordination analysis of the coordination effect of provincial high-tech industry agglomeration and resource carrying capacity in the Yellow River Basin from 2009 to 2021,The evolution of the geographical and temporal pattern of development was investigated using the Moran index and kernel density estimation.The results show that the agglomeration of high-tech industries in the Yellow River Basin presents a development trend of seek improvement in stability,and there is a good coupling and coordination throughout the progression of scientific and technological innovation and the loading capacity of the resource,from the viewpoint of a time series.From the perspective of spatial pattern distribution,the whole basin aims at the lower reaches,accelerates the optimization of digital industry and promotes Yellow River Basin development of superior quality through innovation support and increase of input,and based on policy guidance.

Socio-economic and energy-environmental impacts of technological change on China's agricultural development under the carbon neutrality strategy

Promoting agricultural modernisation through technological change is an important strategy for China.China's carbon neutrality strategy is leading to systemic socio-economic changes that could exacerbate the uncertainty of agricultural development.Therefore,applying a computable general equilibrium(CGE)model,this study characterises the agricultural sector in detail,introducing endogenous technological change proxied by research and development(R&D)to assess the impact of different technological change scenarios on agricultural development under the carbon neutrality target.The results show that allocating carbon revenue for R&D inputs can mitigate the significant negative impact of achieving carbon neutrality on knowledge capital and production in agricultural sectors.Overall,using carbon revenue only for R&D input in crop sectors has the optimal effect on increasing the agricultural sectors'knowledge capital,improving crop production and profit,reducing crop external dependence and promoting the synergistic reduction of carbon and pollutant emissions.However,this scenario has the largest negative impact on macro-economics and household welfare.In contrast,allocating carbon revenue to promote technological change in broader non-energy sectors or both crops and non-energy sectors can effectively mitigate negative socio-economic impacts,but the positive impact on agricultural development is minimal.These findings provide practical insights for the rational use of carbon revenue to expand agricultural R&D investment and ensure balanced agricultural and economic development under the carbon neutrality target.

Challenges and opportunities for battery health estimation:Bridging laboratory research and real-world applications

Addressing climate change demands a significant shift away from fossil fuels,with sectors like electricity and transportation relying heavily on renewable energy.Integral to this transition are energy storage systems,notably lithium-ion batteries.Over time,these batteries degrade,affecting their efficiency and posing safety risks.Monitoring and predicting battery aging is essential,especially estimating its state of health(SOH).Various SOH estimation methods exist,from traditional model-based approaches to machine learning approaches.

Policy and Management of Carbon Peaking and Carbon Neutrality:A Literature Review

The vision of reaching a carbon peak and achieving carbon neutrality is guiding the low-carbon transition of China’s socioeconomic system.Currently,a research gap remains in the existing literature in terms of studies that systematically identify opportunities to achieve carbon neutrality.To address this gap,this study comprehensively collates and investigates 1105 published research studies regarding carbon peaking and carbon neutrality.In doing so,the principles of development in this area are quantitively analyzed from a space–time perspective.At the same time,this study traces shifts and alterations in research hotspots.This systematic review summarizes the priorities and standpoints of key industries on carbon peaking and carbon neutrality.Furthermore,with an emphasis on five key management science topics,the scientific concerns and strategic demands for these two carbon emission-reduction goals are clarified.The paper ends with theoretical insights on and practical countermeasures for actions,priority tasks,and policy measures that will enable China to achieve a carbon-neutral future.This study provides a complete picture of the research status on carbon peaking and carbon neutrality,as well as the research directions worth investigating in this field,which are crucial to the formulation of carbon peak and carbon neutrality policies.

Trade Benefits and Environmental Costs of GVCS: A Case Study of the BRICS

As the international trading system has developed with the division of Global value Chains (GVCS), the export trade of Brazil, Russia, India, China, and South Africa (BRICS) has grown rapidly. The resulting growth of carbon emissions has drawn wide attention from the international community, necessitating the comparison of the trade benefits and environmental costs of the BRICS participation in GVCS. Based on the Eora database, this paper constructs a decomposition framework for the calculation of export value-added and embodied carbon, based on a multi-region input-output (MRIO) model. The trade benefits and environmental costs paid by the BRICS’ total exports from 1990 to 2015 were measured and the imbalance was analyzed, along with the causes. The results show that the main value-added and carbon embodied in the BRICS’ exports originate from their own countries, and the domestic value-added content of the BRICS’ exports decreased while the foreign value-added content increased.

Impact of carbon disclosure on debt financing costs

Creditors,such as banks,often use disclosed environmental information to assess a company’s environmental risk and ensure the safety of debt funds.Consequently,carbon disclosures have become an important consideration for creditors when making investments.This study explores the relationship between carbon disclosure and debt financing costs using data on listed companies from 2008 to 2019.The results show that carbon disclosure can reduce the debt financing costs of enterprises,and that this influence is more significant for private companies than for state-owned enterprises.Instrumental variables and Propensity Score Matching(PSM)were used to evaluate the robustness of negative relationships.Furthermore,carbon disclosure has a more significant impact on debt costs with less environmental supervision pressure,weak residents’environmental awareness,and weak product market competition.These findings provide guidance for companies’carbon information disclosure and support the establishment of official carbon disclosure standards.

Transformation power or development pressure:economic growth targets and urban carbon productivity

Maintaining moderate economic growth targets(EGTs)is the key for local governments to effectively implement the“carbon peak and carbon neutrality”goals under the refreshed development pattern.Utilizing panel data of 276 prefecture-level cities in China's Mainland from 2010 to 2020,and employing methods such as intermediary and threshold models,this study empirically analyzes the internal mechanism of EGT’s impact on urban carbon productivity(UCP).Our findings demonstrate that:①The overall EGT during the analyzed period is not conducive to improving UCP.This conclusion remains valid after a series of robustness tests.This effect is more pronounced in the central region and resource-based cities than in the east-west region and non resource-based cities.②EGT not only directly suppresses UCP but also exerts indirect negative impacts on UCP from three aspects:delaying the digital economy(DE),constraining financial expansion(FE),and hindering green technology innovation(GTI).This negative indirect effect is similar to or even surpasses the direct effect,suggesting that the internal relationship between EGT and“dual-carbon”goals should be re-evaluated from a new compound perspective.③EGT not only has a simple linear impact on UCP but also significantly exhibits a dynamic evolution pattern in inverted“U”shape.That is,as EGT continuously upgrades,a nonlinear impact on UCP emerges in the form of“promoting first,suppressing later”.This indicates that surpassing the“degree”limit for EGT will be detrimental to the improvement of UCP.This study broadens the scope of carbon productivity analysis by introducing a new perspective centered on EGT.The insights gleaned from this research offer valuable guidance for local governments to effectively manage economic growth expectations and promote the synchronized achievement of dual-carbon objectives.

Provoking Buying Behaviors Amid Crises:Unfolding the Underlying Mechanisms of Psychological Impairments

Crises in the past have caused devastating,long-lasting impacts on the global economy.The after-effects always bring some dynamic and rigorous challenges for businesses and governments.Such challenges have always been a point of discussion for scholars.The recent COVID-19 pandemic emaciated the global economy,leaving everyone mired in uncertainty,fear,and psychological impairments.One of the headwind features utilized by consumers during pandemic was panic buying(PB),which must be explored in various contexts for policymakers and practitioners.To address this gap,this study deployed a moderated mediation mechanism,integrating the health belief model(HBM)and competitive arousal theory(CAT)to excavate the notions underlying PB with the intrusion of evolved real-time psychological disorders:intolerance of uncertainty(IU)and cyberchondria(CYC).The study was conducted as a natural experiment in a South Asian developing economy using online surveys.It found that health beliefs—perceived severity(PSV)and perceived susceptibility(PSC)—positively impact perceived arousal(PA),which causes PB,and that PA has a sturdy mediator role.Moreover,in the relationship between health beliefs and arousal,the different psychological disorders were found to have significant moderating roles The study findings can help mitigate risk uncertainties and panic situations and thus contribute to consumers’wellbeing.

Productivity effect and overuse of pesticide in crop production in China

Chinese farmers are often accused of overusing pesticides that play a crucial role in enhancing crop yield by reducing losses to crop pests. Pesticide overuse has caused a series of negative health and environmental externalities. This paper quantiifes the productivity effect and the optimal amount of pesticides in rice, cotton and maize production in China from the economic perspective. Using survey data col ected in 2012 and 2013, both Cobb-Douglas and Weibul damage control speciifcations are used to estimate the production function. Results show that pesticides have statistical y signiifcant pro-ductivity effect on crop yield. On the condition of Weibul damage control speciifcations, the marginal products of 1 kg of the active ingredients of pesticides for rice, cotton and maize are 71.06, 22.73 and 98.45 kg, respectively. However, 57, 64 and 17%of the actual amount of pesticides are overused for rice, cotton and maize, respectively. Moreover, the productivity effect of pesticides would be overestimated using Cobb-Douglas speciifcation without incorporating a damage control agent.

Rice variety improvement and the contribution of foreign germplasms in China

The introduction and use of foreign germplasms have played an important role in the improvement of crop varieties in China. Based on published materials and scientist interviews, we collected data on the sown area, morphological characteristics, and pedigree of the popular rice varieties grown in the 15 major rice production provinces and 1 autonomous region in China, from 1982 to 2011. Results showed that China＇s scientists developed the largest number of rice varieties worldwide, and that rice yield potential and grain quality have substantiality improved during the studied period. In contrast, resistance of newly-released varieties to diseases and insect pests has decreased since the 1990s. Germplasms from the Interna- tional Rice Research Institute （IRRI） and from Japan have contributed 16.4 and 11.2% of genetic materials to China＇s rice varieties developed between 1982 and 2011, respectively. While IRRI＇s materials contributed to the improvement of yield potential, growth duration, and blast and bacterial blight resistance, Japanese materials contributed to the improvement of grain quality. Materials from other countries contributed to the improvement of resistance to diseases and insect pests, particularly to rice blast disease, brown planthoppers, white-backed planthoppers, and striped stem borers.

Equivalency and unbiasedness of grey prediction models

In order to deeply research the structure discrepancy and modeling mechanism among different grey prediction models, the equivalence and unbiasedness of grey prediction models are analyzed and verified. The results show that all the grey prediction models that are strictly derived from x^（0）（k） ＋az^（1）（k） = b have the identical model structure and simulation precision. Moreover, the unbiased simulation for the homogeneous exponential sequence can be accomplished. However, the models derived from dx^（1）/dt ＋ ax^（1）= b are only close to those derived from x^（0）（k） ＋ az^（1）（k） = b provided that ｜a｜ has to satisfy｜a｜ 0.1; neither could the unbiased simulation for the homogeneous exponential sequence be achieved. The above conclusions are proved and verified through some theorems and examples.

Divisia Decomposition Method and Its Application to Changes of Net Oil Import Intensity

The existing oil import dependence index cannot exactly measure the economic cost or scales, and it is difficult to describe the economical aspect of oil security. To measure the foreign dependence of one country's economy and reflect its oil economic security, this paper defines the net oil import intensity as the ratio of net oil import cost to GDP. By using Divisia Index Decomposition, the change of net oil import intensity in five industrialized countries and five newly industrialized countries during 1971—2010 is decomposed into five factors: oil price, oil intensity, oil self-sufficiency, domestic price level and exchange rate. The result shows that the dominating factors are oil price and oil intensity; moreover, the newly industrialized countries have higher net oil import intensity than industrialized countries.

Optimization of total harmonic current distortion and torque pulsation reduction in high-power induction motors using genetic algorithms

This paper presents a powerful application of genetic algorithm （GA） for the minimization of the total harmonic current distortion （THCD） in high-power induction motors fed by voltage source inverters, based on an approximate harmonic model. That is, having defined a desired fundamental output voltage, optimal pulse patterns （switching angles） are determined to produce the fundamental output voltage while minimizing the THCD. The complete results for the two cases of three and five switching instants in the first quarter period of pulse width modulation （PWM） waveform are presented. Presence of harmonics in the stator excitation leads to a pulsing-torque component. Considering the fact that if the pulsing-torques are at low frequencies, they can cause troublesome speed fluctuations, shaft fatigue, and unsatisfactory performance in the feedback control system, the 5th, 7th, 1 lth, and 13th current harmonics （in the case of five switching angles） are constrained at some pre-specified values, to mitigate the detrimental effects of low-frequency harmonics. At the same time, the THCD is optimized while the required fundamental output voltage is maintained.

Safety-Critical System Reliability Modeling and Their Analyses in Terms of Effects of Component Failure Modes

New models of safety-critical systems are built here. In these systems, when components fail, different defect states have different effects, hence need different ways to measure. In the models, there are two kinds of failure modes of the components： one could be called failed-safe, and the other may be named failed- dangerous In practice, the so-called failed-dangerous components may lead a system to peril. However, failed-safe components will not. Reliability and safety issues are analyzed using Ion-Channel modeling theory to get count of repairs and time duration before the system becomes dangerous. In the closing section a numerical example is presented to illustrate the results obtained in the paper.

Formalization and Verification of Business Process Modeling Based on UML and Petri Nets

In order to provide a quantitative analysis and verification method for activity diagrams based business process modeling, a formal definition of activity diagrams is introduced. And the basic requirements for activity diagrams based business process models are proposed. Furthermore, the standardized transformation technique between business process models and basic Petri nets is presented and the analysis method for the soundness and well-structured properties of business processes is introduced.

Energy Efficiency and Emissions Reduction Potential of China's Industrial Sector

Based on the total-factor energy efficiency framework,this paper calculates China's industrial energy efficiency and CO2 emissions reduction potential from 2000 to 2009 by utilizing the directional distance function and data envelopment analysis.The empirical results show that:China's industrial overall energy efficiency is relatively lower while the emis-sions reduction potential is relatively greater,given the optimum production frontier.Significant indus-trial disparities of energy efficiency and emissions reduction potential exist.Energy efficiency and emis-sions reduction potential significantly show different tendencies of industrial dynamic variation.This paper suggests the Chinese government impose differential carbon taxes,flexibly utilize carbon market mecha-nism,strengthen energy-saving technological R&D,promote the utilization of renewable energy,and strengthen environmental supervision and regulation,so as to improve China's industrial energy efficiency and reduce CO2 emissions.

The decoupling relationship between China’s economic growth and carbon emissions from the perspective of industrial structure

This study analyses the decoupling relationship between energy-related CO_(2) emissions and economic growth in China from 2000-2017 from the perspective of industrial structure using the LMDI method and Tapio decoupling model.The decoupling driving force was decomposed into emission,energy intensity,industrial structure,economic activity,and population factors.Studies have shown that the restructuring of China’s industries has not led to a significant increase in CO_(2) emissions.Specifically,from 2000 to 2017,China’s economic development and carbon emissions are generally in a weak decoupling state.Strong decoupling occurred from 2000 to 2001 and from 2013 to 2016.The industrial structure change has a substantial impact on the primary sector(agriculture),followed by the tertiary sector(services),while the impact on the secondary sector(industry)is negligible.The GDP contribution of the primary industry is small,but it is an indispensable guarantee for a country.With the development of agricultural mechanization and technology,human and animal power in this industry has been decreasing year by year,and large-scale planting has improved energy efficiency.The level of technology should be continuously strengthened to promote the decoupling of carbon emissions.The contribution of the secondary industry to GDP is around 40%,but the secondary industry accounts for more than 80%of CO_(2) emissions,mainly caused by the use of fossil energy.In 2017,fossil energy still accounted for about 86.2%of China’s energy consumption,so fossil energy remains the most critical energy source for China’s economic development.Coal,in turn,accounts for the largest share of fossil energy consumption.Therefore,emphasis should be placed on increasing technological innovation and conversion from fossil to non-fossil energy sources.The Chinese government considers the service industry a new engine for sustainable social and economic development.The contribution of the tertiary sector to GDP has increased from 2000 to 2017,followed by resource and environmental problems.Although the current share of CO_(2) emissions directly caused by the tertiary sector is not high,as the tertiary sector continues to grow,plans to reduce the decoupling of carbon emissions from the tertiary sector should be made in advance.

Impact of meteorological conditions and PM2.5 on the onset of acute aortic dissection in monsoonal climate

Objective To investigate the impact of meteorological conditions and PM2.5 on the onset of acute aortic dissection in monsoonal climate. Methods A linear regression analysis was performed in monsoonal climate epidemiological survey for a period of four years on the impact of meteorological factors （minimal temperature, mean temperature, maximal temperature, average daily surface temperature, day temperature range, relative humidity, mean wind speed, and atmospheric pressure） and PM2.5 concentration on the daily incidences of acute aortic dissections. Meteorological variables and PM2.5 concentration were retrieved on a daily basis from Beijing Regional Climate Center and the Ministry of Environmental Protection of the People’s Republic of China’s website, and the daily incidences of acute aortic dissections were retrieved from the Clinical Data Analysis and Reporting System in the Emergency and Critical Care Center of Beijing Anzhen Hospital. Results During the study period （from January 2011 to December 2014）, 1164 patients were identified as having acute aortic dissections. The corresponding incidences in spring and autumn were 0.96 and 1.00, respectively, which significantly higher than that in summer and winter. The incidences of acute aortic dissection in a day could be predicted by diurnal temperature range （DTR） using the following linear multiple regression models： incidences of acute aortic dissection = 0.543 ＋ 0.025 × DTR. Conclusion This is the first study to show an attributable effect of DTR on acute aortic events in monsoonal climate. Our study confirms that meteorological variables were important factors influencing the incidence of acute aortic dissection.